Metabolic profiling assisted quality assessment of Rhodiola rosea extracts by high-performance liquid chromatography

In this work, fast and sensitive high-performance liquid chromatography (HPLC) coupled with multivariate analysis was utilized to assist the quality assessment of Rhodiola rosea extracts (RREs). 131 peaks were separated and detected in RREs on a fused-core C18 column. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) of the chromatographic data demonstrated that 10 batches of RREs could be well-differentiated and categorized into three groups which were closely related to the origins of RREs. Partial least square-discriminant analysis (PLS-DA) showed that the quality differentiation might be explained by at least 6 components, in which rosavin was characterized by an external reference, rosiridine was identified by liquid chromatography-mass spectrometry (LC-MS), and the mass spectra of the others were provided. The observation that the level of rosavin was more relevant to the multivariate chromatographic data than the ones of salidroside and tyrosol, the other two components commonly used to standardize RREs, was confirmed by the PLS prediction models. Results of the present study not only indicated that rosavin was a rational marker to represent the quality of RREs, but also demonstrated the power of HPLC-based metabolic profiling in the quality assessment of herbal extracts.